ENGLISH

Human Face Recognition Using Third-Order Synthetic Neural Networks

By Okechukwu A. Uwechue , Abhijit S. Pandya (auth.)

Book information

Publisher
Springer US
Year
1997
ISBN
978-1-4613-6832-8, 978-1-4615-4092-2
DOI
10.1007/978-1-4615-4092-2
Language
english
Format
PDF
Filesize
5 MB (5273942 bytes)
Series
The Springer International Series in Engineering and Computer Science 410
Edition
1
Pages
123\131
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Dynamical Systems and Complexity;Computer ImagingMultimedia Information Systems;Statistical PhysicsPattern Recognition and Graphics;Image ProcessingVision

Description

Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

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